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Probability-Based Multi-objective Optimization for Material Selection


Probability-Based Multi-objective Optimization for Material Selection



von: Maosheng Zheng, Haipeng Teng, Jie Yu, Ying Cui, Yi Wang

96,29 €

Verlag: Springer
Format: PDF
Veröffentl.: 12.08.2022
ISBN/EAN: 9789811933516
Sprache: englisch

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Beschreibungen

<p>This book illuminates the fundamental principle and applications of probability-based&nbsp;multi-objective&nbsp;optimization for material selection systematically, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies, such as response surface methodology, orthogonal experimental design, and uniform experimental design, are all performed; the conditions of the material performance utility with desirable value and robust assessment are included; the discretization treatment of complicated integral in the evaluation is presented. </p>

<p>The authors wish this work will cast a brick to attract jade and would make its contributions to relevant fields as a paving stone.</p>

<p>This book can be used as a textbook for postgraduate and advanced undergraduate students in material relevant majors, and a reference book for scientists and engineers digging in the related fields.</p>
Chapter 1 Introduction<div><br></div><div>It introduces the general idea of multiple objective optimization in material selection, the status of the applications of multiple objective optimization in material selection, the previous methods and their shortcomings, etc.</div><div><br></div><div><br></div><div>Chapter 2 Probability-Based Multi-Objective Optimization and Applications</div><div><br></div><div>It describes the general idea of probability-based multiple objective optimization, the basis of theoretic meaning in probability theory, the algorithm, and the features, etc. Applications of materials selection, and some other applications in more broader and general issues are given.</div><div><br></div><div><br></div><div>Chapter 3 Extension in Condition of the Utility with Interval Number</div><div><br></div><div>It describes the extension of probability-based multiple objective optimization in condition of the utility with interval number, some applications of materials selection are given.</div><div><br></div><div><br></div><div>Chapter 4 Extension in Condition of the Utility with Desirable Value</div><div><br></div><div>It describes the extension of probability-based multiple objective optimization in condition of the utility with desirable value, some applications of materials selection are given.</div><div><br></div><div><br></div><div>Chapter 5 Combination of Probability-Based Multi-Objective Optimization with Test Design Methods</div><div><br></div><div>It describes the combination of probability-based multi-objective optimization with test design methods, such as orthogonal test design and uniform experimental design. Some applications of materials selection are given.</div><div><br></div><div><br></div><div>Chapter 6 Application of Regression Analysis in the Probability-Based Multi-Objective Optimization</div><div><br></div><div>Regression analysis is applied to the probability-based multi-objective optimization, it provides a more accurate prediction, especially for test design methods. Some applications of materials selection are given.</div><div><br></div><div><br></div><div>Chapter 7 Concluding Remarks</div><div><br></div><div>Conclusion of this book and reviewing the up-to-date progress.</div>
<p><b>Dr. Maosheng Zheng</b> received his Bachelor degree in Theoretical Physics from Northwest University, Xi’an, China, in 1983, Master degree in Electronic Physics from Xidian University, Xi’an, China, in 1985, and Ph.D. degree in Materials Science and Engineering from Northwestern Polytechnic University, Xi’an, China, in 1992. In June 1994 to June 2006, Dr. Zheng has been in School of Materials Science and Engineering, Xi’an Jiaotong University as a Professor, and since June 2006, Dr. Zheng has been in School of Chemical Engineering, Northwest University as a Professor.</p>

<p>Dr. Zheng focuses on the research of Materials Science and Technology. His recent research interests include: material selection with multi – objective optimization, material technology, energy resource material and technology, renewable energy conversion and utilization, etc. Till 2021, Dr. Zheng has published 2 monographs (1<sup>st</sup> authored, Springer; coauthored, Science Press) more than 230 peer-reviewed papers in international journals and conferences, chaired “863” project and many projects of Sci. & Tech. Ministry and Shaanxi Province of China. He is a Member of China Energy Society, Vice Chairman of Shaanxi Corrosion and Protection Society, and served as a Reviewer of several international journals. He was a recipient of&nbsp;State Council special allowance, 2nd prize of Science and Technology Progress Award of China Aviation Industry Corporation, 3rd prize of Science and Technology Progress Award of the Ministry of Education, 2nd prize of Huo Yingdong Young Teacher (Research), The 2nd Youth Science and Technology Award of Shaanxi Province, 2nd prize of the Natural Science Award of China Higher Education, respectively.&nbsp;</p><p></p><p><b>Dr. Haipeng Teng</b> received his Bachelor degree in Thermal and Power Engineering from Xi'an Jiaotong University, Xi’an, China, in 2002 and Ph.D. degree in Thermal and Power Engineering from Institute of Engineering Thermophysics of Chinese Academy of Sciences, Beijing, China, in 2011. In July 2002 to July 2006, Dr. Teng has been a Teacher in College of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology. In July 2011, Dr. Teng started as a Lecturer in School of Chemical Engineering, Northwest University, and an Associate Professor in 2014.</p>

Dr. Teng focuses on the research of energy resource material, thermal energy conversion and utilization, renewable energy, etc. Till 2021, Dr. Teng has published 1 monograph (co-authored, Springer) and more than 30 peer-reviewed papers in international journals and conferences, completed more than ten scientific research projects.<p></p><p><b>Jie Yu</b> received her Bachelor degree in polymer science & technology from Northwestern Polytechnic University, Xi’an, China, in 1987. In July 1987 to Dec. 1992, Yu worked at Xi’an Far East Machinery Manufacturing Company as an Assistant Engineer responsible for the design and processing of rubber and plastic parts; in Jan. 1993 to Sept. 2007, Yu served as an Engineer in Department of Polymer Materials of Xi'an Jiaotong University; in Sept. 2007 to Aug. 2020, Yu worked as a Senior Engineer College of Life Sciences of Northwest University; since August 2020, Yu served as a Professor-leveled Senior Engineer at College of Life Sciences of Northwest University.&nbsp;&nbsp;</p>

<p>Jie Yu focuses on the research of polymer materials and their applications in medicine. Till 2021, Yu has published more than 50 scientific research papers, chaired and completed 2 key projects of Shaanxi Province, participated in the completion of 5 national and provincial key projects, and 2 enterprise cooperation projects, obtained national invention patents 3 items, and 2 items have been transformed to serve the society, won 1 advanced worker of Northwest University, 2 science and technology awards of Shaanxi Provincial Higher Education Institutions, and 1 gold medal of Shaanxi Science and Technology Workers Innovation and Entrepreneurship Competition.</p><p><b>Ying Cui</b> received her Bachelor of Mechanical Engineering from Shaanxi University of Technology in July 1996, Master of Industrial Engineering from Sichuan University in 2014. In Aug. 1996 to May 2018, Cui worked at Baoji Equipment Factory of China Railway Electrification Bureau Group Company, and since Feb. 2007 she served as a Senior Engineer. Since May 2018, Cui served as Chief Engineer and Senior Engineer of China Railway Baoji Railway Electrical Equipment Inspection Co. Cui is Engineering and Technical Expert of China Railway Electrification Bureau Group Co., Ltd., first-level procurement expert of China Railway Corporation, and a top talent in Baoji High-tech Zone. Cui has successively engaged in the design, manufacturing, and testing of electrified railways and urban rail contact net products, R & D and testing of mechanical components for electrified railways and urban rail transit; presided over the "Shaanxi Railway Electrical Equipment Testing Service Platform", "Rigid Suspension Anti-seize Device", "Straddle-type Monorail Contact Rail Power Supply System Product Research", and more than 20 key scientific research projects, etc. Presided&nbsp;over the revision of the railway industry standard "Electrified Railway Busbars and Components", participated in the "Rail Transit Rigid Overhead Catenary Project Construction Quality Acceptance Standard" and other standards, and published more than 10 papers, obtained more than 40 patents. Cui won the first prize of Science and Technology Progress of China Railway Engineering Corporation, a number of science and technology awards from the city and group companies.&nbsp;&nbsp;</p><p><b>Yi Wang</b> received her Bachelor degree in Mechanical Design, Manufacturing and Automation from Northwest A & F University, China, in 2014 and Master degree in Mechanical Design and Theory from Xi'an Shiyou University, China, in 2017. Since June 2018, Wang has been in School of Chemical Engineering, Northwest University as an Assistant Engineer engaged mainly in Process Equipment and Control Engineering, since Oct. 2020, she served as an Engineer. Till 2021, Wang has published 1 monograph (co-authored, Springer) and 10 peer-reviewed papers in international journals and conferences.&nbsp;</p><br><p></p>
<p>This book illuminates the fundamental principle and applications of probability-based&nbsp;multi-objective&nbsp;optimization for material selection&nbsp;systematically, in which a brand new concept of preferable probability and its assessment as well as other&nbsp;treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies, such as response surface methodology,&nbsp;orthogonal&nbsp;experimental&nbsp;design, and uniform experimental design, are all performed; the&nbsp;conditions of the material performance utility with desirable value and&nbsp;robust assessment are included; the&nbsp;discretization treatment of complicated integral in the evaluation is presented.</p><p>The authors wish this work will cast a brick to attract jade and would make its contributions to relevant&nbsp;fields as a paving stone.</p><p>This book can be used as a textbook for postgraduate and advanced undergraduate students in material relevant majors, and a reference book for scientists and engineers digging in the related fields.</p>
<p>Illuminates a new method for assessing multi-objective optimization with application examples</p><p>Opens a new way for material selection, multi-objective orthogonal experimental design and uniform experimental design</p><p>Involves no personal or other subjective coefficients in the new method</p>

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